Contour Matching Method for SAR Images Based on Salient Contour Features

In the research of matching navigation and precision guidance using spaceborne SAR image as the reference image and airborne/missile SAR image as the real- time image, the traditional point feature- based matching method has too many feature points, high mismatch rate, and easy affected by problems such as noise and gray level changes. A new method for matching SAR remote sensing images from coarse to fine based on salient contour features is proposed. Based on the pre-processing of SAR images, an improved Fuzzy C-Means (FCM) clustering image segmentation is used to to extract closed contour features. Then, a normalized contour center distance descriptor is constructed for two- way matching to obtain the rough matching contours with strong robustness. Finally, the improved Local Binary Pattern (LBP) operator is employed on the rough matching contours to gain the fine matching result. The experimental results demonstrate the proposed method has the advantages of high accuracy and strong robustness in the case of image rotation, spatial variation and noise interference, and is suitable for remote sensing SAR image matching.